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index.html
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<html>
<head>
<meta http-equiv=Content-Type content="text/html; charset=utf-8">
<meta name=Generator content="Microsoft Word 15 (filtered)">
<style>
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<div class=WordSection1>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><b><span
lang=EN style='font-size:19.0pt;line-height:150%;font-family:"Playfair Display"'> </span></b></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><b><span
lang=EN style='font-size:19.0pt;line-height:150%;font-family:"Playfair Display"'> </span></b></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><b><span
lang=EN style='font-size:19.0pt;line-height:150%;font-family:"Playfair Display"'>Automatic
Mineral Detection on Lunar Surface </span></b></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'> </span></b></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'>Presented
by: Insha M and Niveditha C V</span></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'>Under
the guidance of Dr Guneshwar Thangjam</span></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'>Course
Instructor: Dr Subhankar Mishra</span></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><span
lang=EN style='font-size:13.0pt;line-height:150%;font-family:"Playfair Display"'> </span></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><span
lang=EN style='font-size:13.0pt;line-height:150%;font-family:"Playfair Display"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comic Sans MS"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comic Sans MS"'> </span><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>The
reflectance spectra of a material contains information about its physical and
chemical properties as it tells how the material interacts with light. In this
project, we analyse the reflectance data obtained from the M3 (Moon Mineralogy
Mapper) hyperspectral data of the Chandrayaan-I mission.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'> </span></b></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>SCIENTIFIC PROBLEM AND IDEA:</span></b></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'> </span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> The radiance
spectra we observe from the hyperspectral data has the reflectance measured by
the sensors of all the materials within its field of view and so contains the
spectral feature of the mixture. Our goal is to identify the minerals
contributing to the mixed spectra. The major minerals that we are interested in
are orthopyroxene, clinopyroxene, plagioclase, olivine, spinel, ilmenite and
their mixtures.</span></p>
<p class=MsoNormal><span lang=EN style='font-size:14.0pt;line-height:115%;
font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> To identify
them, we are using classification methods to classify spectrum into its
absorption feature classes using machine learning algorithms. The mineral
classification will be done using SVM and other classifiers which will be taken
after cross-validation.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>RELEVANT LITERATURE:</span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Aaron E. Maxwell, Timothy A. Warner & Fang
Fang (2018) Implementation of machine-learning classification in remote
sensing: an applied review, International Journal of Remote Sensing, 39:9,
2784-2817, DOI: 10.1080/01431161.2018.1433343</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>R. O. Green et al.(2011)The Moon Mineralogy
Mapper (M3) imaging spectrometer for lunar science: Instrument description,
calibration, on‐orbit measurements, science data calibration and on‐orbit
validation,doi:10.1029/2011JE003797</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Julien Maitre, Kévin Bouchard, L. Paul
Bédard(2019) Mineral grains recognition using computer vision and machine
learning, Computers & Geosciences, Volume 130,2019, Pages 84-93, ISSN
0098-3004, https://doi.org/10.1016/j.cageo.2019.05.009.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>DATASET:</span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:4.5pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>The
dataset that we are using is measured by the Moon Mineralogy Mapper image
spectrometer onboard the Chandrayaan-1 Mission. The spectral range of this is
430nm to 3000nm with 10 nm spectral sampling and a 24-degree field of view. The
dataset we are taking is Level 2 corrected i.e the raw data is processed with
corrections, removing the thermal emission, photometric correction and ground
truth correction.</span></p>
<p class=MsoNormal style='margin-left:4.5pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:4.5pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>MACHINE LEARNING ALGORITHMS:</span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>We are using machine
learning algorithms in this project to detect the presence of different
minerals on the lunar surface.</span></p>
<p class=MsoNormal><span lang=EN style='font-size:14.0pt;line-height:115%;
font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>We are using both
supervised and unsupervised algorithms. We will be mainly using Support Vector
Machine with kernel and other classifier algorithms for minimizing error and
improving accuracy.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'> </span></b></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>METHODOLOGY, TIMELINE AND WORK
DISTRIBUTION:</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK 6:
Preprocessing of M3 data: (Niveditha)</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Includes
data cleaning, data integration, data reduction, and data transformation.</span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK 7
& 8: End-member collection: (Insha)</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Our
focus will be on the different combinations of techniques used to derive the
physical, chemical, and mineralogical information from the spectra.</span></p>
<p class=MsoNormal align=center style='margin-bottom:16.0pt;text-align:center;
line-height:150%'><span lang=EN style='font-size:12.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>-------------------- M I D W A Y P R E S E
N T A T I O N -------------------- </span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK 9
& 10: Feature engineering: (Niveditha)</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Pre-processing
of existing features, adding new features, and selecting the best features or
combination of features based on feature importance and the requirements of
machine learning algorithms.</span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK
11: Classification using ML algorithm: (Insha)</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Applying
the selected Machine Learning algorithms on the dataset for the required
classifications.</span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK
12: Result analysis and Conclusion: ( Insha and Niveditha )</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Observing
and then analysing the results we obtained and concluding our project.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>EXPECTED RESULTS:</span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Detection of the mineral composition of the
lunar surface using machine learning algorithms.</span></p>
<p class=MsoNormal style='margin-left:.5in;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Comparative study of the machine learning
algorithms used.</span></p>
<p class=MsoNormal style='margin-left:.5in;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Analysis of the mineral composition for
understanding the chemical composition of the moon where the minerals under
study are orthopyroxene, clinopyroxene, plagioclase, olivine, spinel, ilmenite
and their mixtures.</span></p>
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<p class=MsoNormal align=center style='text-align:center;line-height:150%'><b><span
lang=EN style='font-size:19.0pt;line-height:150%;font-family:"Playfair Display"'> </span></b></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><b><span
lang=EN style='font-size:19.0pt;line-height:150%;font-family:"Playfair Display"'> </span></b></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><b><span
lang=EN style='font-size:19.0pt;line-height:150%;font-family:"Playfair Display"'>Automatic
Mineral Detection on Lunar Surface </span></b></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'> </span></b></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'>Presented
by: Insha M and Niveditha C V</span></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'>Under
the guidance of Dr Guneshwar Thangjam</span></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal align=center style='text-align:center'><span lang=EN
style='font-size:14.0pt;line-height:115%;font-family:"Comfortaa Regular"'>Course
Instructor: Dr Subhankar Mishra</span></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><span
lang=EN style='font-size:13.0pt;line-height:150%;font-family:"Playfair Display"'> </span></p>
<p class=MsoNormal align=center style='text-align:center;line-height:150%'><span
lang=EN style='font-size:13.0pt;line-height:150%;font-family:"Playfair Display"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comic Sans MS"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comic Sans MS"'> </span><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>The
reflectance spectra of a material contains information about its physical and
chemical properties as it tells how the material interacts with light. In this
project, we analyse the reflectance data obtained from the M3 (Moon Mineralogy
Mapper) hyperspectral data of the Chandrayaan-I mission.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'> </span></b></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>SCIENTIFIC PROBLEM AND IDEA:</span></b></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'> </span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> The radiance
spectra we observe from the hyperspectral data has the reflectance measured by
the sensors of all the materials within its field of view and so contains the
spectral feature of the mixture. Our goal is to identify the minerals
contributing to the mixed spectra. The major minerals that we are interested in
are orthopyroxene, clinopyroxene, plagioclase, olivine, spinel, ilmenite and
their mixtures.</span></p>
<p class=MsoNormal><span lang=EN style='font-size:14.0pt;line-height:115%;
font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> To identify
them, we are using classification methods to classify spectrum into its
absorption feature classes using machine learning algorithms. The mineral
classification will be done using SVM and other classifiers which will be taken
after cross-validation.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>RELEVANT LITERATURE:</span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Aaron E. Maxwell, Timothy A. Warner & Fang
Fang (2018) Implementation of machine-learning classification in remote
sensing: an applied review, International Journal of Remote Sensing, 39:9,
2784-2817, DOI: 10.1080/01431161.2018.1433343</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>R. O. Green et al.(2011)The Moon Mineralogy
Mapper (M3) imaging spectrometer for lunar science: Instrument description,
calibration, on‐orbit measurements, science data calibration and on‐orbit
validation,doi:10.1029/2011JE003797</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Julien Maitre, Kévin Bouchard, L. Paul
Bédard(2019) Mineral grains recognition using computer vision and machine
learning, Computers & Geosciences, Volume 130,2019, Pages 84-93, ISSN
0098-3004, https://doi.org/10.1016/j.cageo.2019.05.009.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>DATASET:</span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:4.5pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>The
dataset that we are using is measured by the Moon Mineralogy Mapper image
spectrometer onboard the Chandrayaan-1 Mission. The spectral range of this is
430nm to 3000nm with 10 nm spectral sampling and a 24-degree field of view. The
dataset we are taking is Level 2 corrected i.e the raw data is processed with
corrections, removing the thermal emission, photometric correction and ground
truth correction.</span></p>
<p class=MsoNormal style='margin-left:4.5pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:4.5pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>MACHINE LEARNING ALGORITHMS:</span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>We are using machine
learning algorithms in this project to detect the presence of different
minerals on the lunar surface.</span></p>
<p class=MsoNormal><span lang=EN style='font-size:14.0pt;line-height:115%;
font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>We are using both
supervised and unsupervised algorithms. We will be mainly using Support Vector
Machine with kernel and other classifier algorithms for minimizing error and
improving accuracy.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'> </span></b></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>METHODOLOGY, TIMELINE AND WORK
DISTRIBUTION:</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK 6:
Preprocessing of M3 data: (Niveditha)</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Includes
data cleaning, data integration, data reduction, and data transformation.</span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK 7
& 8: End-member collection: (Insha)</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Our
focus will be on the different combinations of techniques used to derive the
physical, chemical, and mineralogical information from the spectra.</span></p>
<p class=MsoNormal align=center style='margin-bottom:16.0pt;text-align:center;
line-height:150%'><span lang=EN style='font-size:12.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>-------------------- M I D W A Y P R E S E
N T A T I O N -------------------- </span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK 9
& 10: Feature engineering: (Niveditha)</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Pre-processing
of existing features, adding new features, and selecting the best features or
combination of features based on feature importance and the requirements of
machine learning algorithms.</span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK
11: Classification using ML algorithm: (Insha)</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Applying
the selected Machine Learning algorithms on the dataset for the required
classifications.</span></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><b><span
lang=EN style='font-size:14.0pt;line-height:150%;font-family:Comfortaa'>WEEK
12: Result analysis and Conclusion: ( Insha and Niveditha )</span></b></p>
<p class=MsoNormal style='margin-bottom:16.0pt;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'>Observing
and then analysing the results we obtained and concluding our project.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='line-height:150%'><b><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:Comfortaa'>EXPECTED RESULTS:</span></b></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Detection of the mineral composition of the
lunar surface using machine learning algorithms.</span></p>
<p class=MsoNormal style='margin-left:.5in;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Comparative study of the machine learning
algorithms used.</span></p>
<p class=MsoNormal style='margin-left:.5in;line-height:150%'><span lang=EN
style='font-size:14.0pt;line-height:150%;font-family:"Comfortaa Regular"'> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.5in;line-height:150%'><span
lang=EN style='font-size:14.0pt;line-height:150%;color:black'><span
style='font:7.0pt "Times New Roman"'> </span>❏<span
style='font:7.0pt "Times New Roman"'>
</span></span><span lang=EN style='font-size:14.0pt;line-height:150%;
font-family:"Comfortaa Regular"'>Analysis of the mineral composition for
understanding the chemical composition of the moon where the minerals under
study are orthopyroxene, clinopyroxene, plagioclase, olivine, spinel, ilmenite
and their mixtures.</span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comic Sans MS"'> </span></p>
<p class=MsoNormal style='line-height:150%'><span lang=EN style='font-size:
14.0pt;line-height:150%;font-family:"Comic Sans MS"'> </span></p>
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